CRAN/E | missForestPredict

missForestPredict

Missing Value Imputation using Random Forest for Prediction Settings

Installation

About

Missing data imputation based on the 'missForest' algorithm (Stekhoven, Daniel J (2012) doi:10.1093/bioinformatics/btr597) with adaptations for prediction settings. The function missForest() is used to impute a (training) dataset with missing values and to learn imputation models that can be later used for imputing new observations. The function missForestPredict() is used to impute one or multiple new observations (test set) using the models learned on the training data.

github.com/sibipx/missForestPredict

Key Metrics

Version 1.0
R ≥ 4.0
Published 2023-12-12 277 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks missForestPredict results

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Maintainer

Maintainer

Elena Albu

Authors

Elena Albu

aut / cre

Material

Reference manual
Package source

Vignettes

missForestPredict convergence criteria and error monitoring
Using the missForestPredict package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 4.0

Imports

ranger
methods
stats

Suggests

knitr
rmarkdown
ggplot2
dplyr
tidyr